Foissac Frantz, Bouazza Naïm, Valade Elodie, De Sousa Mendes Mailys, Fauchet Floris, Benaboud Sihem, Hirt Déborah, Tréluyer Jean-Marc, Urien Saïk
EA 08, Université Paris Descartes, Sorbonne Paris Cité, France.
Unité de Recherche Clinique, Assistance Publique Hôpitaux de Paris (APHP), Hôpital Tarnier, Paris, France.
J Clin Pharmacol. 2015 Jul;55(7):739-47. doi: 10.1002/jcph.488. Epub 2015 May 25.
The pediatric population is often exposed to drugs without sufficient knowledge about pharmacokinetics. The prediction of accurate clearance values in children, especially in neonates and infants, will improve the rational in dosing decisions. Drug clearances from birth to adulthood were compiled after a systematic review of pharmacokinetic reports. The analysis was performed using NONMEM. Clearance predictions were then evaluated by external validation. Prediction errors were also compared with those obtained from weight-based allometric scaling and physiologically based clearance (PBCL) models. For the analysis, 17 and 15 drugs were used for model building and external validation, respectively. A model based on the adult drug clearance value and taking into account both weight and age was retained. Age-related maturation of clearance reached 90% of the adult value within 1.5 years of life. For children less than 2 years old, allometric scaling alone systematically overestimated clearances. Accounting for age improved the clearance prediction in the 6 months-2 years age group (prediction error < 25%). Predictions obtained from the PBCL approach were close to our results. This analysis established a single equation using the adult clearance value as well as individual age and weight to predict drug clearance in children older than 6 months.
儿科人群常常在对药物动力学缺乏足够了解的情况下接触药物。准确预测儿童,尤其是新生儿和婴儿的清除率值,将有助于改进给药决策的合理性。在对药物动力学报告进行系统综述后,汇总了从出生到成年的药物清除率。使用NONMEM进行分析。然后通过外部验证评估清除率预测。还将预测误差与基于体重的异速生长标度法和基于生理学的清除率(PBCL)模型所得的误差进行了比较。分析中,分别使用17种和15种药物进行模型构建和外部验证。保留了一个基于成人药物清除率值并同时考虑体重和年龄的模型。清除率与年龄相关的成熟在1.5岁时达到成人值的90%。对于2岁以下儿童,仅用异速生长标度法会系统性高估清除率。考虑年龄可改善6个月至2岁年龄组的清除率预测(预测误差<25%)。从PBCL方法获得的预测与我们的结果相近。该分析建立了一个单一方程,使用成人清除率值以及个体年龄和体重来预测6个月以上儿童的药物清除率。